Fire control attack scheme optimization based on BP network and ordinal optimization

Fire control attack scheme optimization is one of the simulation optimization problems. Considering the large calculative load and a great time cost required for traditional optimization algorithms, the ordinal optimization theory is used to narrow down the searching space and improve the searching efficiency. Firstly, an accurate evaluation model which is on the basis of missile acquisition probability is established. Secondly, the neural network based on back propagation (BP) fitted is treated as the rough evaluation model. Finally, the ordinal optimization is used to search a better attack scheme which reaches a certain acquisition probability. The example analysis shows that the ordinal optimization can find a good scheme in high probability and improve the searching efficiency effectively.